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ECML
2004
Springer
15 years 3 months ago
Efficient Hyperkernel Learning Using Second-Order Cone Programming
The kernel function plays a central role in kernel methods. Most existing methods can only adapt the kernel parameters or the kernel matrix based on empirical data. Recently, Ong e...
Ivor W. Tsang, James T. Kwok
PKDD
2010
Springer
179views Data Mining» more  PKDD 2010»
14 years 9 months ago
Gaussian Processes for Sample Efficient Reinforcement Learning with RMAX-Like Exploration
Abstract. We present an implementation of model-based online reinforcement learning (RL) for continuous domains with deterministic transitions that is specifically designed to achi...
Tobias Jung, Peter Stone
AAAI
1993
15 years 1 months ago
Finding Accurate Frontiers: A Knowledge-Intensive Approach to Relational Learning
learning (EBL) component. In this paper we provide a brief review of FOIL and FOCL, then discuss how operationalizing a domain theory can adversely affect the accuracy of a learned...
Michael J. Pazzani, Clifford Brunk
PKDD
2010
Springer
160views Data Mining» more  PKDD 2010»
14 years 10 months ago
Entropy and Margin Maximization for Structured Output Learning
Abstract. We consider the problem of training discriminative structured output predictors, such as conditional random fields (CRFs) and structured support vector machines (SSVMs)....
Patrick Pletscher, Cheng Soon Ong, Joachim M. Buhm...
IFIP12
2008
15 years 1 months ago
A Study with Class Imbalance and Random Sampling for a Decision Tree Learning System
Sampling methods are a direct approach to tackle the problem of class imbalance. These methods sample a data set in order to alter the class distributions. Usually these methods ar...
Ronaldo C. Prati, Gustavo E. A. P. A. Batista, Mar...